Grifols have announced proof-of-concept data from its Chronos-PD programme, which uses AI, advanced proteomics and real-world data to identify early signs of Parkinson’s disease (PD).
The data demonstrates that individuals with PD experience biological changes over a decade before clinical diagnosis, allowing for potential early diagnosis and intervention in the future.
Affecting nearly one million people in the US and nearly six million worldwide, PD occurs when the brain cells that make dopamine stop working or die. Understanding of the causes of the disease remains limited despite decades of research and treatment advancement.
Funded by the Michael J. Fox Foundation for Parkinson’s Research (MJFF), the study is the most deeply profiled longitudinal proteomic study in PD to date, with over 2,600 longitudinal plasma samples and over 25,000 protein types analysed using four complementary proteomics platforms.
After analysing longitudinal plasma samples covering a period of up to 12 years before the diagnosis of PD and nine years afterwards in the pilot study, researchers were able to track the evolution of distinct plasma proteins in people with PD. This information has the potential to help establish an early-warning system for PD.
Researchers have confirmed PD biomarkers previously discovered and identified reproducible early PD biomarkers, validated across up to five independent cohorts. The study also uncovered novel, early biomarkers of PD, including a major modulation of the CXCL12–cell adhesion molecules–integrin axis, a signalling network that governs leukocyte trafficking and blood-brain barrier integrity and is implicated in PD-associated neuroinflammation.
Jörg Schüttrumpf, Grifols Chief Scientific Innovation Office, said: “This new proof-of-concept data offers additional insights into the biology and progression of PD, years before clinical detection.
“The results also validate the Chronos platform, with potential applications beyond PD. Going back in time to search for the earliest signs of disease can help accelerate and ultimately develop new diagnostics and disease-modifying therapeutics.”